You are currently viewing an archived version of Topic Simulation Modeling.
If updates or revisions have been published you can find them at Simulation Modeling.
Learning Objectives:
Conduct an experiment using simulation techniques from an activity perspective
Explain how a simulation from an activity perspective can be used in transportation
Discuss important computational laboratory tools for creating new models and visualizing model simulations and model outcomes
Discuss whether, when prior information is absent, repeatedly generating random synthetic datasets can be used to provide statistical significance
Discuss Monte Carlo simulation use in GIS&T
Discuss effective scientific use of supervisory genetic algorithms with agent-based simulation models
Describe how supervisory search and optimization methods can be used to analyze key characteristics of initial conditions and results and to optimize results based on systematic targeted search through the parameter and random seed spaces
You are currently viewing an archived version of Topic Simulation Modeling. If updates or revisions have been published you can find them at Simulation Modeling.